Matlab IIR filter implementation Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern) Announcing the arrival of Valued Associate #679: Cesar Manara Unicorn Meta Zoo #1: Why another podcast?Matlab code demonstrating use of fft (Fast Fourier Transform)2D convolution in matlabRational Approximation for e with MatlabLess For, more MATLABesque?Linear interpolation Matlab to C++Optimizing C++ equivalent of Matlab `filter` functionParzen window density estimation in MATLABOptimizing MATLAB LoopMedian Filter Implementation In PythonApplying correction to a time series in Matlab
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Matlab IIR filter implementation
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Matlab code demonstrating use of fft (Fast Fourier Transform)2D convolution in matlabRational Approximation for e with MatlabLess For, more MATLABesque?Linear interpolation Matlab to C++Optimizing C++ equivalent of Matlab `filter` functionParzen window density estimation in MATLABOptimizing MATLAB LoopMedian Filter Implementation In PythonApplying correction to a time series in Matlab
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$begingroup$
I need to implement the Matlab filter(b,a,x) function in Java. Before I do this, I would like to rewrite the function in Matlab before translating into Java. So far, writing out all the coefficients works really well. See below:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize); % b coefficient - a is unused
i = 1;
for n = length(b) : length(x) % yes I know I am losing my first 10 samples
y(i,:) = [ b(1)*x(n) + b(2)*x(n-1) + b(3)*x(n-2) + b(4)*x(n-3) + ...
b(5)*x(n-4) + b(6)*x(n-5) + b(7)*x(n-6) + b(8)*x(n-7) + ...
b(9)*x(n-8) + b(10)*x(n-9) ];
i = i+1; % used for indexing calculated results into new array
end
However, I want the loop contents to automatically update when I change the window size. In the above example, if I were to increase the windowsize by a factor of two, then I would have to write out twice as many multiples of b and x within the for loop. Which is a terrible solution to my problem. Please advise.
matlab signal-processing
$endgroup$
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I need to implement the Matlab filter(b,a,x) function in Java. Before I do this, I would like to rewrite the function in Matlab before translating into Java. So far, writing out all the coefficients works really well. See below:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize); % b coefficient - a is unused
i = 1;
for n = length(b) : length(x) % yes I know I am losing my first 10 samples
y(i,:) = [ b(1)*x(n) + b(2)*x(n-1) + b(3)*x(n-2) + b(4)*x(n-3) + ...
b(5)*x(n-4) + b(6)*x(n-5) + b(7)*x(n-6) + b(8)*x(n-7) + ...
b(9)*x(n-8) + b(10)*x(n-9) ];
i = i+1; % used for indexing calculated results into new array
end
However, I want the loop contents to automatically update when I change the window size. In the above example, if I were to increase the windowsize by a factor of two, then I would have to write out twice as many multiples of b and x within the for loop. Which is a terrible solution to my problem. Please advise.
matlab signal-processing
$endgroup$
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I need to implement the Matlab filter(b,a,x) function in Java. Before I do this, I would like to rewrite the function in Matlab before translating into Java. So far, writing out all the coefficients works really well. See below:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize); % b coefficient - a is unused
i = 1;
for n = length(b) : length(x) % yes I know I am losing my first 10 samples
y(i,:) = [ b(1)*x(n) + b(2)*x(n-1) + b(3)*x(n-2) + b(4)*x(n-3) + ...
b(5)*x(n-4) + b(6)*x(n-5) + b(7)*x(n-6) + b(8)*x(n-7) + ...
b(9)*x(n-8) + b(10)*x(n-9) ];
i = i+1; % used for indexing calculated results into new array
end
However, I want the loop contents to automatically update when I change the window size. In the above example, if I were to increase the windowsize by a factor of two, then I would have to write out twice as many multiples of b and x within the for loop. Which is a terrible solution to my problem. Please advise.
matlab signal-processing
$endgroup$
I need to implement the Matlab filter(b,a,x) function in Java. Before I do this, I would like to rewrite the function in Matlab before translating into Java. So far, writing out all the coefficients works really well. See below:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize); % b coefficient - a is unused
i = 1;
for n = length(b) : length(x) % yes I know I am losing my first 10 samples
y(i,:) = [ b(1)*x(n) + b(2)*x(n-1) + b(3)*x(n-2) + b(4)*x(n-3) + ...
b(5)*x(n-4) + b(6)*x(n-5) + b(7)*x(n-6) + b(8)*x(n-7) + ...
b(9)*x(n-8) + b(10)*x(n-9) ];
i = i+1; % used for indexing calculated results into new array
end
However, I want the loop contents to automatically update when I change the window size. In the above example, if I were to increase the windowsize by a factor of two, then I would have to write out twice as many multiples of b and x within the for loop. Which is a terrible solution to my problem. Please advise.
matlab signal-processing
matlab signal-processing
edited Feb 24 '18 at 16:33
Christopher Byrne
asked Feb 23 '18 at 13:56
Christopher ByrneChristopher Byrne
162
162
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
So this solution works:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize);
i = 1;
for n = windowSize: length(x)
m = 0;
tempSum = 0;
for j = 1 : windowSize
temp = b(j)*x(n-m);
tempSum = tempSum + temp;
m = m + 1;
end
y(i,:) = [tempSum]
i = i+1;
end
See results below:
Instead of having really inaccurate results in the beginning I just skip these. It's important to note that you are losing an amount of samples equal to the number of b coefficients in this solution. So make sure to rescale the X-axis.
Results were compared using Matlabs C = setdiff(y,yy) function and found no difference between the proposed solution and Matlabs filter(b,a,x) function.
$endgroup$
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
add a comment |
Your Answer
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1 Answer
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1 Answer
1
active
oldest
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active
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votes
$begingroup$
So this solution works:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize);
i = 1;
for n = windowSize: length(x)
m = 0;
tempSum = 0;
for j = 1 : windowSize
temp = b(j)*x(n-m);
tempSum = tempSum + temp;
m = m + 1;
end
y(i,:) = [tempSum]
i = i+1;
end
See results below:
Instead of having really inaccurate results in the beginning I just skip these. It's important to note that you are losing an amount of samples equal to the number of b coefficients in this solution. So make sure to rescale the X-axis.
Results were compared using Matlabs C = setdiff(y,yy) function and found no difference between the proposed solution and Matlabs filter(b,a,x) function.
$endgroup$
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
add a comment |
$begingroup$
So this solution works:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize);
i = 1;
for n = windowSize: length(x)
m = 0;
tempSum = 0;
for j = 1 : windowSize
temp = b(j)*x(n-m);
tempSum = tempSum + temp;
m = m + 1;
end
y(i,:) = [tempSum]
i = i+1;
end
See results below:
Instead of having really inaccurate results in the beginning I just skip these. It's important to note that you are losing an amount of samples equal to the number of b coefficients in this solution. So make sure to rescale the X-axis.
Results were compared using Matlabs C = setdiff(y,yy) function and found no difference between the proposed solution and Matlabs filter(b,a,x) function.
$endgroup$
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
add a comment |
$begingroup$
So this solution works:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize);
i = 1;
for n = windowSize: length(x)
m = 0;
tempSum = 0;
for j = 1 : windowSize
temp = b(j)*x(n-m);
tempSum = tempSum + temp;
m = m + 1;
end
y(i,:) = [tempSum]
i = i+1;
end
See results below:
Instead of having really inaccurate results in the beginning I just skip these. It's important to note that you are losing an amount of samples equal to the number of b coefficients in this solution. So make sure to rescale the X-axis.
Results were compared using Matlabs C = setdiff(y,yy) function and found no difference between the proposed solution and Matlabs filter(b,a,x) function.
$endgroup$
So this solution works:
x = load('data.csv');
windowSize = 10;
b = (1/windowSize)*ones(1,windowSize);
i = 1;
for n = windowSize: length(x)
m = 0;
tempSum = 0;
for j = 1 : windowSize
temp = b(j)*x(n-m);
tempSum = tempSum + temp;
m = m + 1;
end
y(i,:) = [tempSum]
i = i+1;
end
See results below:
Instead of having really inaccurate results in the beginning I just skip these. It's important to note that you are losing an amount of samples equal to the number of b coefficients in this solution. So make sure to rescale the X-axis.
Results were compared using Matlabs C = setdiff(y,yy) function and found no difference between the proposed solution and Matlabs filter(b,a,x) function.
answered Feb 24 '18 at 16:46
Christopher ByrneChristopher Byrne
162
162
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
add a comment |
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
$begingroup$
There are much better ans simpler ways to implement Box Filter. If this is all you need, you can get much better.
$endgroup$
– Royi
Feb 8 at 16:52
add a comment |
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